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A review on estimation of stochastic differential equations for pharmacokinetic/pharmacodynamic models

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  • Donnet, Sophie
  • Samson, Adeline
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    Abstract

    This paper is a survey of existing estimation methods for pharmacokinetic/pharmacodynamic (PK/PD) models based on stochastic differential equations (SDEs). Most parametric estimation methods proposed for SDEs require high frequency data and are often poorly suited for PK/PD data which are usually sparse. Moreover, PK/PD experiments generally include not a single individual but a group of subjects, leading to a population estimation approach. This review concentrates on estimation methods which have been applied to PK/PD data, for SDEs observed with and without measurement noise, with a standard or a population approach. Besides, the adopted methodologies highly differ depending on the existence or not of an explicit transition density of the SDE solution.

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    File URL: http://basepub.dauphine.fr/xmlui/bitstream/123456789/11429/2/article_SDE_PKPD-1.pdf
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    Bibliographic Info

    Paper provided by Paris Dauphine University in its series Economics Papers from University Paris Dauphine with number 123456789/11429.

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    Date of creation: 2013
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    Publication status: Published in Advanced Drug Delivery Reviews, 2013, Vol. 65, no. 7. pp. 929-939.Length: 10 pages
    Handle: RePEc:dau:papers:123456789/11429

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    Related research

    Keywords: Stochastic differential equations; Pharmacokinetic; Pharmacodynamic; population approach; maximum likelihood estimation; Kalman Filter; EM algorithm; Hermite expansion; Gauss quadrature; Bayesian estimation;

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    1. Christophe Andrieu & Arnaud Doucet & Roman Holenstein, 2010. "Particle Markov chain Monte Carlo methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(3), pages 269-342.
    2. Benjamin Favetto & Adeline Samson, 2010. "Parameter Estimation for a Bidimensional Partially Observed Ornstein-Uhlenbeck Process with Biological Application," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 37(2), pages 200-220.
    3. Egorov, Alexei V. & Li, Haitao & Xu, Yuewu, 2003. "Maximum likelihood estimation of time-inhomogeneous diffusions," Journal of Econometrics, Elsevier, Elsevier, vol. 114(1), pages 107-139, May.
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